Urology Department, Naval & Veterans Hospital of Athens, Athens, Greece.
Low Urin Tract Symptoms. 2020 Sep;12(3):190-197. doi: 10.1111/luts.12301. Epub 2020 Jan 30.
Currently, the diagnostic ability of uroflowmetry, the most widely used urodynamic test available for initial assessment of patients with lower urinary tract symptoms (LUTS), is considered limited by its inability to accurately discriminate between the underlying mechanisms of this condition. To improve the diagnostic accuracy of uroflow, we developed a mathematical formula that calculates the flow resistive forces index (QRF), a novel measure of bladder outflow/urethral resistance, and assessed its clinical applicability compared to the maximum flow rate (Q ).
A cross-sectional observational study was conducted in a cohort of 61 adult men presenting with voiding dysfunction symptoms, who all underwent free uroflowmetry followed by pressure flow study. The development of the mathematical formula which contains five key uroflowmetry variables (voided volume, flow time, Q , average flow rate, and peak flow time) was based on the assumption that urine volume momentum changes during voiding, the concept of diphasic uroflow pattern (acceleration/deceleration), and the urethral resistance factor (URA) equation. Study subjects were classified either as obstructed or nonobstructed according to established urodynamic criteria (linearized passive urethral resistance relation, LinPURR; Abrams-Griffiths number, AGN [also called bladder outlet obstruction index, BOOI]; and URA). Univariate linear correlations, binary logistic regression model, and receiver operating characteristic (ROC) curve statistical analysis were employed (SPSS-22, MedCalc, GraphPad [P < .05]).
Outflow obstruction was diagnosed in 50.8% (1 in 2) patients. Univariate analysis, and bivariate linear correlation, binary logistic regression, and ROC curve analyses showed that the QRF was a strong independent predictor of bladder outlet/outflow obstruction (BOO), significantly outperforming Q .
QRF index accurately predicts BOO, significantly outperforming the currently widely used bladder outlet obstruction estimator Q . Despite potential study limitations (mainly small cohort size and lack of control group), we anticipate that with further study and proper clinical validation, QRF could become a valuable complement to uroflowmetry.
目前，尿流率测定（Uroflowmetry）是最广泛用于初始评估下尿路症状（LUTS）患者的尿动力学测试，但其无法准确区分该疾病的潜在机制，因此其诊断能力受到限制。为了提高尿流率的诊断准确性，我们开发了一种数学公式，该公式计算流量阻力指数（QRF），这是一种新的膀胱流出/尿道阻力测量指标，并评估其与最大流量（Q）相比的临床适用性。
对 61 名出现排尿功能障碍症状的成年男性进行了一项横断面观察性研究，所有患者均进行了自由尿流率测定，随后进行了压力流研究。该数学公式的开发基于以下假设：在排尿过程中，尿液量的动量发生变化，尿流呈双相模式（加速/减速），以及尿道阻力因子（URA）方程。根据既定的尿动力学标准（线性化被动尿道阻力关系、LinPURR；Abrams-Griffiths 数、AGN[也称为膀胱出口梗阻指数、BOOI]；和 URA），研究对象被分为梗阻组和非梗阻组。采用单变量线性相关性、二元逻辑回归模型和接受者操作特征（ROC）曲线统计分析（SPSS-22、MedCalc、GraphPad[P <.05]）。
50.8%（1/2）的患者被诊断为流出道梗阻。单变量分析、双变量线性相关性、二元逻辑回归和 ROC 曲线分析表明，QRF 是膀胱出口/流出道梗阻（BOO）的强有力独立预测因子，明显优于 Q。
QRF 指数能准确预测 BOO，明显优于目前广泛使用的膀胱出口梗阻估计值 Q。尽管存在潜在的研究局限性（主要是样本量小和缺乏对照组），但我们预计随着进一步研究和适当的临床验证，QRF 可能成为尿流率测定的有益补充。
